Uncertainties and external disturbances such as load disturbance in controlling the speed of induction motor are the main factors for design controller.
1) Fuzzy logic is a Nonlinear system but PID is a liner system so the performance of fuzzy is better than PID
2)In an uncertainty system, nonlinear control is better than linear control
3)The output of the fuzzy logic controller can be controlled because of the fuzzy set
4)It is well known that fuzzy is more complex compared to PID and more computational but nowadays no issues with complexity. There are advanced microprocessor controllers such as DSpace 1104 and 1103. These controllers are fast with a large capacity of memory so no issues with computational of fuzzy. That is why simplified rules of fuzzy logic controllers are designed to reduce the computational burden of the fuzzy logic controller and the complexity of the system.
Hi Qazwan Abdullah غزوان عبد الله محمد طربوش
One obvious advantage is that a PID controller can accommodate only three inputs (e, ∫e, de) and one output, whereas the Fuzzy controller can accommodate as many inputs and many outputs as you wish and your system can handle.
For example, if you have some information about the uncertainties and the external disturbances that you want to take into account, then you can accommodate the info as inputs to the Fuzzy controller.
I would like to share this one with you guys for discussion :
advantages of the fuzzy logic controller over the PID controller
1) Fuzzy logic is a Nonlinear system but PID is a liner system so the performance of fuzzy is better than PID
2)In an uncertainty system, nonlinear control is better than linear control 3)The output of the fuzzy logic controller can be controlled because of the fuzzy set
4)It is well known that fuzzy is more complex compared to PID and more computational but nowadays no issues with complexity. There are advanced microprocessor controllers such as DSpace 1104 and 1103. These controllers are fast with a large capacity of memory so no issues with computational of fuzzy. That is why simplified rules of fuzzy logic controllers are designed to reduce the computational burden of the fuzzy logic controller and the complexity of the system.
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